In this chapter limitations about various segmentation methods will be discussed which methods have already discussed in chapter 2. First of all the need of segmentation over MR images should be known, though there are so many limitations presents in Magnetic Resonance Imaging (MRI) such as: Partial Volume Radio Frequency Noise Intensity homogeneities Gradients Motion Wrap Around Gibbs Ringing Susceptibility There are some disadvantages are also occurs in MRI: MR acquisition takes considerably longer time as compared to CT. In case of MR it is more difficult to obtain uniform image quality. The presence of an implant or other metallic object sometimes makes it difficult to obtain clear images. Patient movement can have the same effect. MRI may not always distinguish between cancer tissue and fluid, known as edema. If …show more content…
This algorithm is combination of fuzzy C means and genetic algorithm because of this combination the process becomes lengthy and very time consuming (Saha Sriparna.et al.2007). In the paper of Indah Soesanti, Adhi Susanto, Thomas Sri Widodo the comparison has shown between K means Fuzzy C Means and FCMS algorithm. This research work was performed on normal brain MRI and glioma brain MRI image (Soesanti Indah.et al.2011) .And the result of this research was that FCMS algorithm was more efficient than K means and FCM algorithm but the limitation of this research was that it was needed spatial information or we can say that authentic information about database. In the paper of Caroline Petit jean , Jean Nicolas Dacher segmentation of cardiac MRI images was included the segmentation of left ventricle only (PetitjeanCaroline.et al.2010 ).According to this research there are less possibilities will occur for segmentation of right ventricle .In this paper research work was based on prior knowledge and this type of segmentation is very